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>>> p = F(x) & G(y) & expr('H(z)')
>>> subst(s1, p)
((F(A) & G(B)) & H(z))
>>> subst(s2, p)
((F(C) & G(y)) & H(x))
>>> subst(s2, subst(s1, p))
((F(A) & G(B)) & H(x))
>>> subst(subst_compose(s1, s2), p)
((F(A) & G(B)) & H(x))
>>> subst(s1, subst(s2, p))
((F(C) & G(B)) & H(A))
>>> subst(subst_compose(s2, s1), p)
((F(C) & G(B)) & H(A))
>>> ppsubst(subst_compose(s1, s2))
{x: A, y: B, z: x}
>>> ppsubst(subst_compose(s2, s1))
{x: C, y: B, z: A}
>>> subst(subst_compose(s1, s2), p) == subst(s2, subst(s1, p))
True
>>> subst(subst_compose(s2, s1), p) == subst(s1, subst(s2, p))
True
"""
result = dict((x, s2.get(v, v)) for x, v in s1.items())
result.update((x, v) for x, v in s2.items() if x not in s1)
return result
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#______________________________________________________________________________
# Example application (not in the book).
# You can use the Expr class to do symbolic differentiation. This used to be
# a part of AI; now it is considered a separate field, Symbolic Algebra.
def diff(y, x):
"""Return the symbolic derivative, dy/dx, as an Expr.
However, you probably want to simplify the results with simp.
>>> diff(x * x, x)
((x * 1) + (x * 1))
>>> simp(diff(x * x, x))
(2 * x)
"""
if y == x: return ONE
elif not y.args: return ZERO
else:
u, op, v = y.args[0], y.op, y.args[-1]
if op == '+': return diff(u, x) + diff(v, x)
elif op == '-' and len(args) == 1: return -diff(u, x)
elif op == '-': return diff(u, x) - diff(v, x)
elif op == '*': return u * diff(v, x) + v * diff(u, x)
elif op == '/': return (v*diff(u, x) - u*diff(v, x)) / (v * v)
elif op == '**' and isnumber(x.op):
return (v * u ** (v - 1) * diff(u, x))
elif op == '**': return (v * u ** (v - 1) * diff(u, x)
+ u ** v * Expr('log')(u) * diff(v, x))
elif op == 'log': return diff(u, x) / u
else: raise ValueError("Unknown op: %s in diff(%s, %s)" % (op, y, x))
def simp(x):
if not x.args: return x
args = map(simp, x.args)
u, op, v = args[0], x.op, args[-1]
if op == '+':
if v == ZERO: return u
if u == ZERO: return v
if u == v: return TWO * u
if u == -v or v == -u: return ZERO
elif op == '-' and len(args) == 1:
if u.op == '-' and len(u.args) == 1: return u.args[0] ## --y ==> y
elif op == '-':
if v == ZERO: return u
if u == ZERO: return -v
if u == v: return ZERO
if u == -v or v == -u: return ZERO
elif op == '*':
if u == ZERO or v == ZERO: return ZERO
if u == ONE: return v
if v == ONE: return u
if u == v: return u ** 2
elif op == '/':
if u == ZERO: return ZERO
if v == ZERO: return Expr('Undefined')
if u == v: return ONE
if u == -v or v == -u: return ZERO
elif op == '**':
if u == ZERO: return ZERO
if v == ZERO: return ONE
if u == ONE: return ONE
if v == ONE: return u
elif op == 'log':
if u == ONE: return ZERO
else: raise ValueError("Unknown op: " + op)
## If we fall through to here, we can not simplify further
return Expr(op, *args)
def d(y, x):
"Differentiate and then simplify."
return simp(diff(y, x))
#_______________________________________________________________________________
# Utilities for doctest cases
# These functions print their arguments in a standard order
# to compensate for the random order in the standard representation
if t is dict: return pretty_dict(x)
elif t is set: return pretty_set(x)
else: return repr(x)
"""Return dictionary d's repr but with the items sorted.
>>> pretty_dict({'m': 'M', 'a': 'A', 'r': 'R', 'k': 'K'})
"{'a': 'A', 'k': 'K', 'm': 'M', 'r': 'R'}"
>>> pretty_dict({z: C, y: B, x: A})
'{x: A, y: B, z: C}'
return '{%s}' % ', '.join('%r: %r' % (k, v)
for k, v in sorted(d.items(), key=repr))
"""Return set s's repr but with the items sorted.
>>> pretty_set(set(['A', 'Q', 'F', 'K', 'Y', 'B']))
"set(['A', 'B', 'F', 'K', 'Q', 'Y'])"
>>> pretty_set(set([z, y, x]))
'set([x, y, z])'
return 'set(%r)' % sorted(s, key=repr)
def pp(x):
print pretty(x)
def ppsubst(s):
"""Pretty-print substitution s"""
ppdict(s)
def ppdict(d):
print pretty_dict(d)
def ppset(s):
print pretty_set(s)
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#________________________________________________________________________
class logicTest: """
### PropKB
>>> kb = PropKB()
>>> kb.tell(A & B)
>>> kb.tell(B >> C)
>>> kb.ask(C) ## The result {} means true, with no substitutions
{}
>>> kb.ask(P)
False
>>> kb.retract(B)
>>> kb.ask(C)
False
>>> pl_true(P, {})
>>> pl_true(P | Q, {P: True})
True
# Notice that the function pl_true cannot reason by cases:
>>> pl_true(P | ~P)
# However, tt_true can:
>>> tt_true(P | ~P)
True
# The following are tautologies from [Fig. 7.11]:
>>> tt_true("(A & B) <=> (B & A)")
True
>>> tt_true("(A | B) <=> (B | A)")
True
>>> tt_true("((A & B) & C) <=> (A & (B & C))")
True
>>> tt_true("((A | B) | C) <=> (A | (B | C))")
True
>>> tt_true("~~A <=> A")
True
>>> tt_true("(A >> B) <=> (~B >> ~A)")
True
>>> tt_true("(A >> B) <=> (~A | B)")
True
>>> tt_true("(A <=> B) <=> ((A >> B) & (B >> A))")
True
>>> tt_true("~(A & B) <=> (~A | ~B)")
True
>>> tt_true("~(A | B) <=> (~A & ~B)")
True
>>> tt_true("(A & (B | C)) <=> ((A & B) | (A & C))")
True
>>> tt_true("(A | (B & C)) <=> ((A | B) & (A | C))")
True
# The following are not tautologies:
>>> tt_true(A & ~A)
False
>>> tt_true(A & B)
False
### [Fig. 7.13]
>>> alpha = expr("~P12")
>>> to_cnf(Fig[7,13] & ~alpha)
((~P12 | B11) & (~P21 | B11) & (P12 | P21 | ~B11) & ~B11 & P12)
>>> tt_entails(Fig[7,13], alpha)
True
>>> pl_resolution(PropKB(Fig[7,13]), alpha)
True
### [Fig. 7.15]
>>> pl_fc_entails(Fig[7,15], expr('SomethingSilly'))
False
### Unification:
>>> unify(x, x, {})
{}
>>> unify(x, 3, {})
{x: 3}
>>> to_cnf((P&Q) | (~P & ~Q))
((~P | P) & (~Q | P) & (~P | Q) & (~Q | Q))
"""